Optimization of a feeder-bus route design by using a multiobjective programming approach

 

Table Of Contents


Chapter ONE

INTRODUCTION

  • 1.1Introduction
  • 1.2Background of Study
  • 1.3Problem Statement
  • 1.4Objective of Study
  • 1.5Limitation of Study
  • 1.6Scope of Study
  • 1.7Significance of Study
  • 1.8Structure of the Research
  • 1.9Definition of Terms

Chapter TWO

LITERATURE REVIEW

  • 2.1Overview of Feeder-Bus Systems
  • 2.2Evolution of Feeder-Bus Route Design
  • 2.3Multiobjective Programming in Transportation
  • 2.4Factors Influencing Feeder-Bus Route Optimization
  • 2.5Case Studies on Feeder-Bus Route Design
  • 2.6Challenges in Feeder-Bus Route Optimization
  • 2.7Benefits of Optimized Feeder-Bus Routes
  • 2.8Integration of Technology in Route Design
  • 2.9Best Practices in Feeder-Bus Route Optimization
  • 2.10Future Trends in Feeder-Bus Transportation

Chapter THREE

RESEARCH METHODOLOGY

  • 3.1Research Methodology Overview
  • 3.2Data Collection Methods
  • 3.3Sampling Techniques
  • 3.4Feasibility Analysis
  • 3.5Mathematical Modeling for Optimization
  • 3.6Software Tools for Analysis
  • 3.7Validation and Testing Procedures
  • 3.8Ethical Considerations in Research

Chapter FOUR

DATA PRESENTATION AND ANALYSIS

  • 4.1Data Analysis and Interpretation
  • 4.2Feasibility Study Results
  • 4.3Optimization Models Implemented
  • 4.4Comparison of Different Route Designs
  • 4.5Impact Assessment of Optimized Routes
  • 4.6Stakeholder Feedback and Recommendations
  • 4.7Cost-Benefit Analysis
  • 4.8Sustainability Assessment

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • 5.1Summary of Findings
  • 5.2Conclusions Drawn from the Study
  • 5.3Recommendations for Future Research
  • 5.4Implications for Feeder-Bus Route Planning
  • 5.5Contributions to Transportation Optimization

Project Abstract

<p> </p><div><div><div></div></div><div><p>This paper presents a feeder-bus route design model, capable of minimizing route length, minimizing maximum route travel time of planned routes, and maximizing service coverage for trip generation. The proposed model considers constraints of route connectivity, subtour prevention, travel time upper bound of a route, relationships between route layout and service coverage, and value ranges of decision variables. Parameter uncertainties are dealt with using fuzzy numbers, and the model is developed as a multiobjective programming problem. A case study of a metro station in Taichung City, Taiwan is then conducted. Next, the programming problem in the case study is solved, based on the technique for order preference by similarity to ideal solution approach to obtain the compromise route design. Results of the case study confirm that the routes of the proposed model perform better than existing routes in terms of network length and service coverage. Additionally, increasing the number of feeder-bus routes decreases maximum route travel time, increases service coverage, and increases network length. To our knowledge, the proposed model is the first bus route design model in the literature to consider simultaneously various stakeholder needs and support for bus route planners in developing alternatives for further evaluation efficiently and systematically.</p></div></div><div><div>Keywords <a target="_blank" rel="nofollow" href="https//www.tandfonline.com/keyword/Feeder-bus+Route+Design">feeder-bus route design</a>, <a target="_blank" rel="nofollow" href="https//www.tandfonline.com/keyword/Link+Covering+Problem">link covering problem</a>, <a target="_blank" rel="nofollow" href="https//www.tandfonline.com/keyword/Optimization">optimization</a>, <a target="_blank" rel="nofollow" href="https//www.tandfonline.com/keyword/Mathematical+Programming">mathematical programming</a>, <a target="_blank" rel="nofollow" href="https//www.tandfonline.com/keyword/TOPSIS">TOPSIS</a>, <a target="_blank" rel="nofollow" href="https//www.tandfonline.com/keyword/Taiwan">Taiwan</a></div></div> <br><p></p>

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